AI Infra Capex is a "Rock and a Hard Place" Situation

Investors have been jittery about possible artificial intelligence circular investment; overinvestment; high capital investment and the sustainability of end user demand for many months, and late October seemed to crystalize some of those fears as key hyperscalers reported quarterly earnings. 

Looking at September 30 through October 30, 2026, one can see the double-digit declines. For about the week ending October 30 technology stocks lost about $1 trillion in valuation.  

Company	Ticker	October stock-price change	Reported Oct. 30 market value ($ billion)	Estimated start-of-month market value ($ billion)	Estimated market value lost ($ billion)
Alphabet	GOOGL	−18.67%	$3,440	$4,230	$790
Nvidia	NVDA	−10.39%	$4,930	$5,502	$572
Meta Platforms	META	−15.19%	$1,570	$1,851	$281
TSMC	TSM	−10.97%	$2,110	$2,370	$260
Micron Technology	MU	−16.92%	$999	$1,203	$204
Broadcom	AVGO	−7.15%	$1,560	$1,680	$120
Amazon	AMZN	−3.53%	$2,600	$2,695	$95

Losses were worse for many suppliers on the chip fabrication, memory or neocloud parts of the value chain. Investors increasingly questioned the return on AI spending. That increases pressure on hyperscalers to reverse course or moderate, but at the risk of abandoning the effort to emerge as a leader of the business. 

Company	Ticker	Reported October stock-price decline
Intel	INTC	−45.20%
CoreWeave	CRWV	−38.05%
SanDisk	SNDK	−35.58%
Nebius Group	NBIS	−33.65%
Lam Research	LRCX	−29.69%
Arm	ARM	−29.54%
Credo Technology	CRDO	−28.16%
Astera Labs	ALAB	−27.42%
Marvell Technology	MRVL	−26.74%
Applied Materials	AMAT	−26.30%

Amazon CEO Andy Jassy calls AI a “once-in-a-lifetime opportunity. I think what we're seeing with AI, it's the biggest transformation in our lifetime.” 

"Would it be more convenient if this type of acceleration and opportunity happened over 25 years and you could spread the CapEx over 25 years," Andy Jassy, Amazon CEO  asked an analyst during the (quarterly earnings) call. "Yeah, it might be more convenient, but that's not the world that we live in, and that's not the opportunity."

That does not help firms keep their profit margins, debt or cash flow where they just recently were, in the short term. But none of the would-be leaders believe they can significantly limit their capital investments at this point without forgoing the opportunity to lead the future market. 

So multiple compression seems likely, as AI infra capex seems to offer a “rock and a hard place” choice.

Are Americans 50% to 70% Less Social Than They Used to Be?

Social isolation seems to be a growing problem, a study by DDB Needham suggests. Between 1975 and 1998, the share of Americans who gave or attended a monthly dinner party declined by half, says DDB Needham as part of its Life Style survey. 

Covid appears to have caused some changes in U.S. social behavior. But many of those changes predate the Covid pandemic.

“The share of Americans who say they host friends or family at their home at least monthly has fallen from 42 percent in 1975 to 12 percent in 2026, a 70 percent collapse in a half-century,” according to Derek Thompson, a Substack contributor. 

Another study suggests that, since 2003 (and up to 2024), the time Americans spend with friends has declined more than 50 percent.

source: American Sociological Association

“Americans have not replaced one form of interaction with another; they have reduced social interaction across the board,” the study authors say. “These findings point to a temporal reorganization of social life marked by the disappearance of the ‘night out.’” 

The U.S. Surgeon General calls this a crisis of loneliness. 

As to “why” this is happening, Bureau of Labor Statistics might well suggest that competition from television, digital entertainment and online communication are drivers of the change, at least in substantial part. 

Simply, staying home has become a more attractive alternative to going out because of streaming, gaming, social media, and online communication. 

And if you have tried to clear calendars for any social event, you know how busy people are, and how many other activities make synchronized face-to-face activities more difficult than once appeared to be the case. 

And some might also note that, as is the case with social media in general, the level of “comparison” in any part of human experience seems to have heightened fears of inadequacy. 

source: Derek Thompson 

In fact, there likely are multiple forces at work that make “staying home” a reasonable choice, compared to going out or entertaining others at home. 

Explanation	Evidence researchers would look for
Digital substitution	Whether increased individual screen time coincides with reduced face-to-face interaction, and whether the two changes are causally related
Work and time pressure	Whether people with irregular schedules, long commutes, or intensive caregiving responsibilities socialize less
Financial pressures	Whether entertaining declines more among households facing higher housing, food, or transportation costs
Geographic separation	Whether distance between friends and relatives predicts fewer visits and gatherings
Institutional decline	Whether loss of church, club, or civic participation predicts weaker friendship networks
COVID-19 habit changes	Whether people whose activities were interrupted returned less often than otherwise similar people whose routines remained intact
Changing preferences	Whether attitudes toward privacy, leisure, and social obligations changed before or after social activity declined

So we might be witnessing an accumulation of several different trends: more attractive solitary entertainment, fragmented schedules, harder-to-coordinate friendships, more demanding expectations for hosting and fewer institutions that routinely bring people together.

source: Data for Progress 

On the other hand, correlation is not necessarily causation. People choosing solitude is one thing;  becoming isolated quite another. 

For lots of reasons, people might genuinely prefer more time alone, as a respite from the rigors of dealing with daily life. 

In other cases social activity might be preferred, but is more difficult to arrange, especially as friends and relatives move about, geographically. 

source: Epoch Times

Either way, many would find the changes unhealthy or unhelpful. 

AI Impact on Revenue, Profits Strongest in IT

A new study by Torsten Slok, partner and chief economist at Apollo Global Management, finds evidence of artificial intelligence financial benefits in the information technology industry, but not elsewhere. “Revenue per worker is rising for the Mag 7 but is flat for the S&P 493,” he says. “Profit margins are rising for the Mag 7 but are flat for the S&P 493” as well. 

source: Apollo

 

source: Apollo

That might fuel concern that AI overinvestment is occurring. On the other hand, it seems also the case that AI investment is highly concentrated in relatively few IT firms. In other words, AI actually is not being deployed at scale outside IT. 

source: Apollo

So observers can take their pick of explanations: either AI is not generally producing measurable results or AI is not yet producing results because few firms outside IT have implemented at scale. 

At a high level, it also is likely that standard statistics miss some meaningful AI-related benefits. In other words, value is created, but not in ways that show up immediately, in every firm or industry, in the form of gross domestic product and productivity growth.

Type of benefit or measurement problem	Example involving AI	What conventional statistics may miss
Free or inexpensive services	A person uses a free chatbot instead of paying for tutoring, research, or basic professional advice.	Consumer value beyond the price paid.
Quality improvement	AI helps a physician explain a diagnosis more clearly or helps a lawyer produce a better analysis.	Better output when the number of services and their recorded prices barely change.
Time savings	A worker completes research in 20 minutes instead of two hours.	The value of saved time if it doesn't translate into recorded production, earnings, or leisure-related output.
New capabilities	A small business gains access to analytical capabilities previously affordable only to large firms.	New economic opportunities that have not yet generated recorded sales.
Intangible investment	A company spends months reorganizing workflows, developing proprietary data, and training employees.	Some of the investment and the resulting organizational capital.
Innovation spillovers	AI accelerates product development, scientific research, or software creation.	Future benefits that have not yet become market transactions or measurable output.
Unpaid or household activity	A consumer uses AI to plan a trip, learn a language, or manage household tasks.	Some of the resulting value because much household production lies outside GDP.

Measurement is itself a problem. The OECD, for example,  identifies intangible investment, cloud-computing accounting, and improvements in the quality and scope of services as important measurement challenges.

Also, value can be produced in economic welfare without showing up in GDP statistics. Such has been the case for many internet-supplied “no extra cost” services used by consumers, for example.

Economists call the difference between what a consumer would be willing to pay and what the consumer actually pays consumer surplus. So a2025 paper by Erik Brynjolfsson and coauthors, GDP-B: Accounting for the Value of New and Free Goods, develops an alternative approach to capturing benefits from free and new goods that standard GDP measures poorly. 

A 2026 Stanford Digital Economy Lab study, What Is Generative AI Worth?, used surveys and incentive-compatible choice experiments to estimate the value U.S. consumers place on access to generative AI tools. Its estimated aggregate consumer surplus rose from $116 billion in 2025 to $172 billion in 2026.

That is unlikely to satisfy skeptics insistent on visible AI impact on firm results. The International Labour Organization's May 2026 research brief, The Aggregation Paradox of AI , finds that strong task-level gains have not yet translated consistently into measurable gains at the firm, sector, or macroeconomic levels. Uneven adoption, workflow constraints, and the cost of organizational change help explain the gap. 

AI might produce large benefits for consumers and workers while capturing relatively little revenue for the companies providing it, as the Apollo analysis suggests is presently the case. 

Or, productivity gains might accrue primarily to a small number of firms, with limited diffusion to the rest of the economy, as the Apollo study also suggests. 

The absence of an immediate productivity boom is not strong evidence that AI is failing, or will fail. Past historical evidence suggests an important new technology takes some time to show benefits. 

But the existence of a historical productivity lag is not strong evidence that a productivity boom is inevitable, either.

Still, a delay in measured economic or firm benefits is not at all unusual. Past innovations such as steam power, electricity,  information technology and the internet have taken some time to generate clear economic value, because:

• Complementary investments in organizational processes, software, training, and new business models must be made

• Benefits may initially be concentrated in particular tasks, firms, and industries

• Some gains, particularly in consumer welfare and intangible assets, are imperfectly captured by conventional statistics.

Financial observers will still remain skeptical. But, as a historical matter, important new general-purpose technologies have almost-always, perhaps always, experienced a lag time between introduction and impact. AI is showing the same pattern.